BSAD 2340 - Data Analysis & Decision Making

Course Syllabus

Instructor: Christine Storlie

Campus address: 1149 Ullsvik Hall

Campus Phone: 608-342-1980

E-mail: storliech@uwplatt.edu

Office Hours: 9 – 10 & 1-2 MWF and 10-noon T-Th

Course Description

Students will learn quantitative decision making skills for managers. Particular focus will be given to

understanding statistics and management science concepts, and developing the skills required to

analyze data, conduct statistical hypothesis testing, and use management science techniques in business

settings.

Prerequisites and Curriculum Program Requirement

Math 1730 or higher. Must meet Excel competency requirement.

Learning Outcomes:

On completion of this course, students will be able to:

Describe the properties of normal, binomial, Poisson, and exponential distributions, provide

examples of when they apply, and perform calculations involving them;

Discriminate between sampling schemes that are generally used in real sampling applications;

Analyze sample data in order to infer the properties of the entire population;

Construct and analyze data files using Excel;

Evaluate data using tables, graphs, and descriptive statistics;

Analyze a single sample of data using hypothesis testing;

Investigate differences in two or more samples using hypothesis testing;

Assess relationships between variables using hypothesis testing;

Perform forecasting scenarios using historical data;

Analyze decision problems that involve uncertainty;

Apply linear programming techniques to business decisions;

Understand how to test the assumptions associated with statistical hypothesis tests; and

Apply statistical analysis and management science techniques to decision making situations.

Textbook: Data Analysis and Decision Making, 5th Edition (2013) by S. Christian Albright; Wayne

Winston; Christopher Zappe. ISBN: 978-111-57528-1

Concepts covered:

Probability and data distributions;

Statistical techniques, including conducting descriptive statistical analyses, creating graphical

data displays and tables, confidence intervals, and hypothesis testing;

Management Science techniques, including decision making under uncertainty, time series

analysis, forecasting, optimization, and simulation;

How to make decisions based on quantitative data analysis; and

How to use Excel to conduct all the analyses listed above.

Activities

Homework Problems: Students will complete homework problems from the text using Excel.

Quizzes & Exams: Quiz and exam material will be based on the text, class lecture, and discussion.

Quizzes will consist of definitions and short answers to questions. Exams will require students to

complete data analysis problems similar to the homework and use the results of the analyses to make

decisions.

In-class Hands-on Activities: As concepts are presented, hands on exercises will be completed in class to

help students apply the concept.

Unit Projects: Unit projects will focus on the application of the analysis techniques covered in the unit to

a hypothetical business situation in order to make a decision. Students will work individually and/or in

teams to complete a data analysis and decision making project that will be presented to the class.

Assessments:

Percent of Grade

Lesson Homework Problems 20%

Lesson Quizzes 15%

Unit Exams 40%

Unit Projects 20%

In-class Hands-on Activities 5%

Course Content:

Unit 1 Introduction to Data Analysis & Decision Making and Exploring Data

Lesson 1 Introduction to Data Analysis and Decision Making

Lesson 2 Describing the Distribution of a Single Variable

Lesson 3 Finding Relationships among Variables

Unit 2 Probability and Decision Making under Uncertainty

Lesson 4 Probability and Probability Distributions

Lesson 5 Normal, Binomial, Poisson, and Exponential Distributions

Lesson 6 Decision Making under Uncertainty

Unit 3 Statistical Inference

Lesson 7 Sampling and Sampling Distributions

Lesson 8 Confidence Interval Estimation

Lesson 9 Hypothesis Testing

Unit 4 Regression Analysis and Time Series Forecasting

Lesson 10 Regression Analysis: Estimating Relationships

Lesson 11 Regression Analysis: Statistical Inference

Lesson 12 Time Series Analysis and Forecasting

Unit 5 Optimization, Simulation Modeling, and Advanced Data Analysis

Lesson 13 Introduction to Optimization Modeling

Lesson 14 Optimization Models

Lesson 15 Introduction to Simulation Modeling

Lesson 16 Simulation Models Lesson 17 Data Mining

Additional Material presented:

Importing Data into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Statistical Reporting

Course Format:

You are responsible for completing assignments, such as reading the textbook and watching videos,

before you come to class so that you are prepared to spend class time using Excel to complete

homework problems, group assignments, and a project for each unit. The homework assignments you

are required to complete will provide you with an understanding of quantitative data analysis

techniques, as well as the knowledge of how to complete the analysis using Microsoft Excel. In class, you

will apply the data analysis techniques to examples from the business world, and then use the results of

the Excel data analyses to make decisions based on real world scenarios. For example, in the unit

projects, you will need to choose the best technique to use to analyze data, analyze the data, interpret

the results in terms of the decision being made, and make the decision. If you do not complete the

assignments before class, you will not understand the material well enough to effectively use Excel to

solve problems from the textbook during class.